For service and diagnostic purposes, work machines are typically equipped with sensors for measuring operating conditions such as engine RPM, oil pressure, water temperature, boost pressure, oil contamination, electric motor current, hydraulic pressure, system voltage, and the like. Further, additional sensors may measure other machine application conditions, such as payload, tire performance, underfoot conditions, and the like. In some cases, storage devices are provided on the work machine to compile a database for later evaluation of machine performance and to aid in diagnosis. Service, operations and production personnel, through the use of a communication service tool, examine the accrued data to get a better picture of the causes of the failure and aid in diagnosis or to evaluate the machine's operation and if it is being operated within defined tolerances such as payload, etc. Similarly, service, operations and production personnel can evaluate the stored data to predict future failures and correct any problems prior to total component failure. In addition, this data may be examined by service, operations, production or other supervisory personnel to evaluate machine and/or operator performance or application severity to ensure maximum productivity of the machine.
Rather than requiring analysis of the data on the machine at the work site, other systems have provided a means for downloading the machine data to a remote database for analysis; collecting the data for several machines may be useful for analyzing the performance of a fleet of machines, and the collection of data in one location may minimize service calls by allowing service personnel to monitor several machines from one location. However, the quantity of diagnostic data which personnel must manually review to diagnose machine issues is vast. Service, operations and production personnel may be able to review all of the data collected from one machine to determine if it is operating normally. However, for the personnel to review all of the data for a fleet of machines in this manner is cost and time prohibitive. There may even be a negative commercial impact with such off-board systems in that the systems are purchased and then not utilized once the complexity of the manual analysis becomes clear. Thus, data is collected and stored, but not analyzed, resulting in failures of the machines or lower machine productivity even though a substantial financial investment has been made in the system.
These issues are particularly relevant to large work machines such as off-highway mining trucks, hydraulic excavators, track-type tractors, wheel loaders, and the like. These machines represent large capital investments and are capable of substantial productivity when operating. It is therefore important to predict failures so servicing can be scheduled during periods in which productivity will be less affected and so minor problems can be repaired before they lead to catastrophic failures, and it is important to monitor machine and operator performance to increase productivity.
The present invention is directed to solving one or more of the problems as set forth above.